Modulation of B <sub>12</sub> Dosage and Response in Fetal Treatment of Methylmalonic Aciduria (MMA): Titration of Treatment Dose to Serum and Urine MMA
Bibliographic record
Abstract
OBJECTIVE: Prenatally diagnosed methylmalonic aciduria (MMA) has been treated in only a few fetuses, and has been done empirically with maternally administered cyanocobalamin (B12) in attempts to ameliorate sequelae that include failure to thrive, developmental delay, dehydration, and coma. There has not been a systematic attempt to titrate doses to fetal response. We investigated the alterations in maternal dosage necessary to keep maternal plasma (MP) and urine (MU) levels of MMA in the normal range secondary to the ability of pharmacological doses of B12 to catalyze the reaction of methylmalonyl-coenzyme A to succinyl-coenzyme A. METHODS: A 28-year-old woman, with a 3-year-old son affected with MMA, underwent amniocentesis at 15 weeks which showed a normal karyotype, elevated amniotic fluid MMA, and decreased amniocyte 5'-deoxyadenosylcobalamin, propionate, and methyl-tetrahydrofolate. MP and MU MMA levels were measured biweekly. B12 doses were altered periodically according to laboratory-determined levels. RESULTS: MP and MU levels varied with gestational age and in response to increases in maternally administered B12. CONCLUSIONS: With increasing gestation, fetal, and placental size, increasing doses of B12 are necessary to maintain MP and MU levels of MMA within normal range. The data suggest that close surveillance and frequent measurements of MMA are necessary to properly titrate B12 treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".